Proving the performance of a new revenue management system

Revenue management (RM) is a complicated business process that can best be described ascontrol of sales (using prices, restrictions, or capacity), usually using software as a tool to aiddecisions. RM software can play a mere informative role, supplying analysts with formatted andsummarized data who use it to make control decisions (setting a price or allocating capacity fora price point), or, play a deeper role, automating the decisions process completely, at the otherextreme. The RM models and algorithms in the academic literature by and large concentrateon the latter, completely automated, level of functionality.A firm considering using a new RM model or RM system needs to evaluate its performance.Academic papers justify the performance of their models using simulations, where customerbooking requests are simulated according to some process and model, and the revenue perfor-mance of the algorithm compared to an alternate set of algorithms. Such simulations, whilean accepted part of the academic literature, and indeed providing research insight, often lackcredibility with management. Even methodologically, they are usually awed, as the simula-tions only test \within-model" performance, and say nothing as to the appropriateness of themodel in the first place. Even simulations that test against alternate models or competition arelimited by their inherent necessity on fixing some model as the universe for their testing. Theseproblems are exacerbated with RM models that attempt to model customer purchase behav-ior or competition, as the right models for competitive actions or customer purchases remainsomewhat of a mystery, or at least with no consensus on their validity.How then to validate a model? Putting it another way, we want to show that a particularmodel or algorithm is the cause of a certain improvement to the RM process compared to theexisting process. We take care to emphasize that we want to prove the said model as the causeof performance, and to compare against a (incumbent) process rather than against an alternatemodel.In this paper we describe a \live" testing experiment that we conducted at Iberia Airlineson a set of flights. A set of competing algorithms control a set of flights during adjacentweeks, and their behavior and results are observed over a relatively long period of time (9months). In parallel, a group of control flights were managed using the traditional mix of manualand algorithmic control (incumbent system). Such \sandbox" testing, while common at manylarge internet search and e-commerce companies is relatively rare in the revenue managementarea. Sandbox testing has an undisputable model of customer behavior but the experimentaldesign and analysis of results is less clear. In this paper we describe the philosophy behind theexperiment, the organizational challenges, the design and setup of the experiment, and outlinethe analysis of the results. This paper is a complement to a (more technical) related paper thatdescribes the econometrics and statistical analysis of the results.

Resting metabolic rate in six- to ten-year-old obese and nonobese children.

The resting metabolic rate (RMR) and body composition of 130 obese and nonobese prepubertal children, aged 6 to 10 years, were assessed by indirect calorimetry and skin-fold thickness, respectively. The mean (+/- SD) RMR was 4619 +/- 449 kJ.day-1 (164 +/- 31 kJ.kg body weight-1 x day-1) in the 62 boys and 4449 +/- 520 kJ.day-1 (147 +/- 32 kJ.kg body weight-1 x day-1) in the 68 girls. Fat-free mass was the best single predictor of RMR (R2 = 0.64; p < 0.001). Step-down multiple regression analysis, with independent variables such as age, gender, weight, and height, allowed several RMR predictive equations to be developed. An equation for boys is as follows: RMR (kJ.day-1) = 1287 + 28.6 x Weight(kg) + 23.6 x Height(cm) - 69.1 x Age(yr) (R2 = 0.58; p < 0.001). An equation for girls is as follows: RMR (kJ.day-1 = 1552 + 35.8 x Weight (kg) + 15.6 x Height (cm) - 36.3 x Age (yr) (R2 = 0.69; p < 0.001). Comparison between the measured RMR and that predicted by currently used formulas showed that most of these equations tended to overestimate the RMR of both genders, especially in overweight children.

The effect of treatment with calcitonin on vertebral fracture rate in osteoporosis.

The efficacy of treatments for osteoporosis does not become evident when evaluated by fracture incidence (FI). Vertebral FI decreased in all controlled studies on calcitonin, but not significantly. Small sample sizes and short periods of treatment may have masked a possible therapeutic benefit, but longer, controlled studies with sodium fluoride or etidronate in larger groups of patients also failed to show a decrease in FI. The present analysis of nine published, therapeutic studies which indicate the FI per year and the initial prevalence of vertebral fractures, examines the question of whether the initial prevalence of fractures has an effect on the subsequent incidence of new fractures and whether the therapeutic effects have to be evaluated as a function of the initial prevalence of fractures. Bearing in mind the differences in roentgenological evaluation and in the size and quality of the various studies, the analysis revealed (1) that in the control groups there was a higher FI in patients with more than three vertebral fractures at baseline (estimated odds ratio (OR) = 49, p = 0.011); (2) that a similar trend, although not statistically significant, was observed in treated patients; (3) that the groups of control patients treated for more than 1 year showed in general an increase in FI beyond the first year and that the reverse was true in treated patients. In conclusion, failure to allow for the initial prevalence of vertebral fractures at the individual level in therapeutic trials of calcitonin to treat osteoporosis and prevent new fractures might have contributed to the absence of a demonstrable benefit of the treatment in those studies.

Constant interest rate projections without the curse of indeterminacy

Constant interest rate (CIR) projections are often criticized on the grounds that they are inconsistent with the existence of a unique equilibrium in a variety of forward-looking models. This note shows howto construct CIR projections that are not subject to that criticism, using a standard New Keynesian model as a reference framework.

Monetary policy and exchange rate volatility in a small open economy

We lay out a small open economy version of the Calvo sticky price model, and show how the equilibrium dynamics can be reduced to simple representation in domestic inflation and the output gap. We use the resulting framework to analyze the macroeconomic implications of three alternative rule-based policy regimes for the small open economy: domestic inflation and CPI-based Taylor rules, and an exchange rate peg. We show that a key difference amongthese regimes lies in the relative amount of exchange rate volatility that they entail. We also discuss a special case for which domestic inflation targeting constitutes the optimal policy, and where a simple second order approximation to the utility of the representative consumer can be derived and used to evaluate the welfare losses associated with the suboptimal rules.

A simple randomized algorithm for consistent sequential prediction of ergodic time series

We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.

Rate of development of forensically-important Dipterain southern Brazil

Dipteran larvae were collected from rabbit (Oryctolagus cunniculus L.) carcasses during the four seasons in 2005 in the southernmost state of Rio Grande do Sul, Brazil. The larvae were fed ground beef at ambient temperatures following collection from carcasses. The development of each species under these conditions was estimated. The most abundant species in the carcasses were Lucilia eximia (Wiedemann) and Chrysomya albiceps (Wiedemann) (Calliphoridae), and they were found in all seasons. The data were fitted to a linear model that describes the relationship between temperature and linear developmental rating. These two species are primary forensic indicators in southern Brazil. Other species such as Hemilucilia semidiaphana (Rondani) (Calliphoridae), Synthesiomyia nudiseta (Wulp), Muscina stabulans (Fallen) (Muscidae), and Fannia pusio (Wiedemann) (Fanniidae) were forensically less important because they only occurred in high frequency in certain seasons and during the first days of carcass decomposition.

On the timing of balance of payments crises: Disaggregated information and interest rate policy

This paper proposes a dynamic framework to study the timing of balance of paymentscrises. The model incorporates two main ingredients: (i) investors have private information; (ii)investors interact in a dynamic setting, weighing the high returns on domestic assets against the incentives to pull out before the devaluation. The model shows that the presence of disaggregated information delays the onset of BOP crises, giving rise to discrete devaluations. It also shows that high interest rates can be eective in delaying and possibly avoiding the abandonment of the peg. The optimal policy is to raise interest rates sharply as fundamentals become very weak. However, this policy is time inconsistent, suggesting a role for commitment devices such as currency boards or IMF pressure.

The rate-limiting step for glucose transport into the hypothalamus is across the blood-hypothalamus interface.

Specialized glucosensing neurons are present in the hypothalamus, some of which neighbor the median eminence, where the blood-brain barrier has been reported leaky. A leaky blood-brain barrier implies high tissue glucose levels and obviates a role for endothelial glucose transporters in the control of hypothalamic glucose concentration, important in understanding the mechanisms of glucose sensing We therefore addressed the question of blood-brain barrier integrity at the hypothalamus for glucose transport by examining the brain tissue-to-plasma glucose ratio in the hypothalamus relative to other brain regions. We also examined glycogenolysis in hypothalamus because its occurrence is unlikely in the potential absence of a hypothalamus-blood interface. Across all regions the concentration of glucose was comparable at a given plasma glucose concentration and was a near linear function of plasma glucose. At steady-state, hypothalamic glucose concentration was similar to the extracellular hypothalamic glucose concentration reported by others. Hypothalamic glycogen fell at a rate of approximately 1.5 micromol/g/h and remained present in substantial amounts. We conclude for the hypothalamus, a putative primary site of brain glucose sensing that: the rate-limiting step for glucose transport into brain cells is at the blood-hypothalamus interface, and that glycogenolysis is consistent with a substantial blood -to- intracellular glucose concentration gradient.

Physiological state and rate protein synthesis of phytoplankton off the coast of Peru as measured by sulfur-35 incorporation

Analiza el estado de la fisiología del fitoplancton de las aguas costeras cercanas a Perú

Productivity growth and the exchange rate regime: The role of financial development

This paper offers empirical evidence that a country's choice of exchange rate regime can have a signifficant impact on its medium-term rate of productivity growth. Moreover, the impact depends critically on the country's level of financial development, its degree of market regulation, and its distance from the global technology frontier. We illustrate how each of these channels may operate in a simple stylized growth model in which real exchange rate uncertainty exacerbates the negative investment e¤ects of domestic credit market constraints. The empirical analysis is based on an 83 country data set spanning the years 1960-2000. Our approach delivers results that are in striking contrast to the vast existing empirical exchange rate literature, which largely finds the effects of exchange rate volatility on real activity to be relatively small and insignificant.

Modeling complex wells with the multi-scale finite-volume method

In this paper, an extension of the multi-scale finite-volume (MSFV) method is devised, which allows to Simulate flow and transport in reservoirs with complex well configurations. The new framework fits nicely into the data Structure of the original MSFV method,and has the important property that large patches covering the whole well are not required. For each well. an additional degree of freedom is introduced. While the treatment of pressure-constraint wells is trivial (the well-bore reference pressure is explicitly specified), additional equations have to be solved to obtain the unknown well-bore pressure of rate-constraint wells. Numerical Simulations of test cases with multiple complex wells demonstrate the ability of the new algorithm to capture the interference between the various wells and the reservoir accurately. (c) 2008 Elsevier Inc. All rights reserved.

Biotic potential and reproductive parameters of Spodoptera eridania (Stoll) (Lepidoptera, Noctuidae) in the laboratory

Biotic potential and reprodutcive parameters of Spodoptera eridania (Stoll) (Lepidoptera, Noctuidae) in the laboratory: This study aimed to evaluate the biotic potential and reproductive parameters of Spodoptera eridania (Stoll, 1782) under controlled conditions (25 ± 1ºC, 70 ± 10% RH and 14 hour photophase). The longevity, pre-, post- and oviposition periods, fecundity and fertility of 15 couples was evaluated. The longevity of females (10.80 days) was not significantly higher than those of males (9.27 days). The mean durations of the pre, post and oviposition periods were 2.067, 0.600 and 8.133 days, respectively. The mean fecundity per female was 1,398 eggs and the mean fertility was 1,367.50 larvae. On average, females copulated 1.133 times. A strong positive correlation was observed between the number of mating and fecundity (r = 0.881, P <0.001). However a strong negative correlation was observed between the number of copulations and the duration of the pre-oviposition period (r = -0.826, P = 0.002) and longevity (r = -0.823, P = 0.001). The biotic potential of S. eridania was estimated at 1.894 x 10(25) individuals/female/year. The net reproductive rate (Ro) was 560.531 times per generation and the mean generation time (T) was 35.807 days. The intrinsic rate of increase (rm) was 0.177, with a finite rate of increase (l) of 1.193, per week

Atrial septal pacing for the termination of atrial fibrillation: study in a biophysical model of human atria.

AIMS: While successful termination by pacing of organized atrial tachycardias has been observed in patients, single site rapid pacing has not yet led to conclusive results for the termination of atrial fibrillation (AF). The purpose of this study was to evaluate a novel atrial septal pacing algorithm for the termination of AF in a biophysical model of the human atria. METHODS AND RESULTS: Sustained AF was generated in a model based on human magnetic resonance images and membrane kinetics. Rapid pacing was applied from the septal area following a dual-stage scheme: (i) rapid pacing for 10-30 s at pacing intervals 62-70% of AF cycle length (AFCL), (ii) slow pacing for 1.5 s at 180% AFCL, initiated by a single stimulus at 130% AFCL. Atrial fibrillation termination success rates were computed. A mean success rate for AF termination of 10.2% was obtained for rapid septal pacing only. The addition of the slow pacing phase increased this rate to 20.2%. At an optimal pacing cycle length (64% AFCL) up to 29% of AF termination was observed. CONCLUSION: The proposed septal pacing algorithm could suppress AF reentries in a more robust way than classical single site rapid pacing. Experimental studies are now needed to determine whether similar termination mechanisms and rates can be observed in animals or humans, and in which types of AF this pacing strategy might be most effective.

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.